R Notebook

lapply(pre2016list, function1)

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This is all well and good. But I found it difficult to remember which zone went where. So I’ve plotted a reference image to go beside the charts. #Pre-2016 Reference Images

arransubsect <- filter(pcs,substr(label,1,4)=="KA27")
lapply(pre2016list, function2)

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But thinking about it, I could plot all the years together like this. #Pre-2016 Individual Zones shown on whole island

lapply(pre2016list, function3)

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Post-2016

lapply(post2016list, function1)

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lapply(post2016list, function2)

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lapply(post2016list, function3)

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Plot the percentiles as bar charts.

arransimd %>%
ggplot(aes(x=year, y=Percentile)) +
  geom_bar(stat="identity") +
  facet_wrap('DataZone') +
  labs(title = "Arran SIMD Datazones", x = "Year", y = "Percentile") +
  theme(plot.title = element_text(hjust = 0.5))

Splitting the bar charts up.

Ideally now I’d like to annotate the above data to highlight the 2016 plots, and show where the change in DZ occurs. (I.e draw a polygon around S01011171-S01011177). I don’t know how to do that yet, so what I’ll do now is seperate it into 2 plots.